class_docstr: This is an adaptor for RNNCell classes to be used with `FusedRNNCell`.
class_docstr_tok: ["This","is","an","adaptor","for","RNNCell","classes","to","be","used","with","`","FusedRNNCell","`","."]
docstr: Initialize the adaptor.
  
  Args:
    cell: an instance of a subclass of a `rnn_cell.RNNCell`.
    use_dynamic_rnn: whether to use dynamic (or static) RNN.
docstr_tok: ["Initialize","the","adaptor",".","Args",":","cell",":","an","instance","of","a","subclass","of","a","`","rnn_cell.RNNCell","`",".","use_dynamic_rnn",":","whether","to","use","dynamic","(","or","static",")","RNN","."]
code: def __init__(self, cell, use_dynamic_rnn=False):
      """Initialize the adaptor.
  
      Args:
        cell: an instance of a subclass of a `rnn_cell.RNNCell`.
        use_dynamic_rnn: whether to use dynamic (or static) RNN.
      """
      self._cell = cell
      self._use_dynamic_rnn = use_dynamic_rnn
  
file_path: spark-nlp/python/sparknlp/training/_tf_graph_builders/tf2contrib/fused_rnn_cell.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import six
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import rnn
label_desc: Use image node_id 1 to create a new FusedRNNCellAdaptor object from inherited base classes: FusedRNNCell with example: obj = FusedRNNCellAdaptor(cell, use_dynamic_rnn)